In taylordunn/dgitheme: DGI Clinical Theme

knitr::opts_chunk$set(
  echo = TRUE,
  collapse = TRUE,
  out.width = "100%")

dgitheme

Provides R functions and templates for plotting and reporting analyses using DGI Clinical company colours.

Installation

# install.package("devtools")
remotes::install_github("taylordunn/dgitheme")

Usage

Reference the documentation with ?dgi_pal, ?dgi_colors and ?scale_color_dgi.

To visualize the color palettes:

scales::show_col(dgi_pal()(3))
scales::show_col(dgi_pal("official")(6))

To return the character hex codes as a vector:

dgi_colors("teal")

ggplot(mtcars, aes(hp, mpg, color = factor(cyl))) +
  geom_point(size = 4) +
  scale_color_manual(values = dgi_colors("teal", "light grey", "black")) +
  theme_minimal()

There are also convenience ggplot2 scale functions:

ggplot(mtcars, aes(hp, mpg, color = factor(cyl))) +
  geom_point(size = 4) +
  scale_color_dgi() +
  theme_minimal()

To create a new RMarkdown document with useful defaults: File -> New File -> R Markdown -> From Template -> DGI RMarkdown Report Template.

Palettes

library(tidyverse)
library(patchwork)

palette_plots <-
  tibble(
    palette = c("main", "cool", "grey", "official",
                "teal white", "teal black", "teal grey",
                "blue white", "blue black", "blue grey",
                "sea green white", "sea green black", "sea green grey",
                "complementary", "split-complementary",
                "triadic", "tetradic", "qualitative"),
    n = c(3, 3, 3, 6,
          6, 6, 6,
          6, 6, 6,
          6, 6, 6,
          2, 3,
          3, 4, 5)
  ) %>%
  mutate(colors = map2(palette, n, ~dgitheme::dgi_pal(.x)(.y))) %>%
  unnest(colors) %>%
  group_by(palette) %>%
  mutate(i = 1:n()) %>%
  nest() %>%
  mutate(
    p = map2(
      palette, data,
      ~ggplot(data = .y,
              aes(x = i, y = 1, fill = reorder(colors, i))) +
        geom_tile() +
        geom_label(aes(label = colors), color = "white", fill = "black",
                   size = 3) +
        scale_fill_manual(values = .y$colors) +
        theme_void() +
        theme(legend.position = "none") +
        labs(title = str_c(.x, " (", nrow(.y), ")"))
    )
  )
reduce(palette_plots$p, `%+%`) +
  plot_layout(ncol = 1)